Creating written text is a major challenge for children who
experience difficulties with the cognitive processes that underpin
writing (Dockrell, 2009); their texts are shorter, more error prone, and
poorly organized compared to those of typically developing peers of the
same age (Hooper, Swarm, Wakely, de Kruif, & Montgomery, 2002;
McArthur & Graham, 1987). These difficulties often continue to
challenge young people through their school career and beyond (Connelly,
Campbell, MacLean, & Barnes, 2006; Riddick, Farmer, & Sterling,
1997). Establishing the ways in which barriers and mediators interact
over time to influence the production of written text for specific
profiles of learning difficulties is a prerequisite to the development
of theory and evidence-based interventions. Using a longitudinal data
set, we examined the relationships of language, literacy, and nonverbal
ability with the written text production of a cohort of young people
with a history of specific language impairment (SLI) at the end of
compulsory education in the United Kingdom (age 16). Practitioners,
policy makers, and researchers use a range of different terms to
describe this population (see Dockrell, Lindsay, Letchford, & Mackie
2006; see also Tomblin et al., 2003, for primary language disorder).
Moreover, different terms are used in Europe (dysphagia) and North
America (SLI in the United States, dysphagia in parts of Canada). The
population is heterogeneous, with the specific nature of their problems
residing with one or more subcomponents of the language system. We use
the term specific language impairment to reflect the most common usage
in the literature.
Children with SLI experience problems with the acquisition and
processing of oral language skills. The most commonly used core
criterion to identify children with SLI is that their language problems
cannot be explained in terms of other cognitive, neurological, or
perceptual deficits (Leonard, 1998). Language problems are evident by a
protracted rate of language development as well as difficulties with
subcomponents of the language system (Leonard). Measurements that tap
into children's proficiencies with phonological processing,
sentence recall, nonword repetition, and tense marking have all
demonstrated high levels of specificity and sensitivity in
differentiating children with SLI from their typically developing peers
(Conti-Ramsden, Botting, & Faragher, 2001; Ellis Weismer et al.,
2000). Although conventionally identified by discrepancy criteria,
children with SLI are heterogeneous in their profile of language
impairments and in terms of nonverbal ability (Botting, Faragher,
Simkin, Knox, & Conti-Ramsden, 2001). Patterns of performance also
vary over time (Botting, 2005; Conti-Ramsden & Botting, 1999). For
many young people with SLI, difficulties with spoken communication
skills persist into adolescence (Beitchman, Wilson, Brownlie, Waiters,
& Lancee, 1996; Botting et al.; Stothard, Snowling, Bishop,
Chipchase, & Kaplan, 1998) and adulthood (Clegg, Hollis, Mawhood,
& Rutter, 2005; Johnson et al., 1999). Older students continue to
experience difficulties with reduced vocabulary levels (Johnson et al.);
accurate use of verb morphology (Clahsen, Bartke, & Gollner, 1997);
and some syntactic structures (Norbury, Bishop, & Briscoe, 2001).
These linguistic deficits have marked effects on the processing of
written text (Bishop & Snowling, 2004), resulting in difficulties in
both word reading and comprehension (Catts, Fey, Tomblin, & Zhang,
2002; Stothard et al., 1998). As with linguistic performance there is
considerable variability within the population on these measures, only
some of which is explained by language competence and cognitive skills
(Young et al., 2002). Variations in phonological and nonphonological
language skills relate to different patterns of reading behavior (Bishop
& Snowling). Phonological processing skills are closely related to
reading decoding (Castles & Coltheart, 2004) and spelling
(Caravolas, Hulme, & Snowling, 2001), whereas measures of receptive
language have been associated with poor reading comprehension (Nation,
Clarke, Marshall, & Durand, 2004). Both receptive and expressive
vocabulary are related to reading performance (Ouellette, 2006;
Tannenbaum, Torgesen, & Wagner, 2006; Wise, Sevcik, Morris, Lovett,
& Wolf, 2007).
Specific relationships between oral language competence and the
production of written text have been reported both for children with
continuing and those with resolved language problems, leading to the
hypothesis that written language can be conceptualized as a window into
residual language problems (Bishop & Clarkson, 2003; Fey, Carts,
Proctor-Williams, Tomblin, & Zhang, 2004). Phonological processes
directly impact children's spelling, a prerequisite to extended
text generation (Berninger, Abbott, Whitaker, Sylvester, & Nolen,
1995). Wider oral language comprehension skills have been implicated as
important factors in the children's text production (Bishop &
Clarkson; Cragg & Nation, 2006; Dockrell, Lindsay, Connelly, &
Mackie, 2007). Vocabulary appears to provide a building block for
written language (see Green et al., 2003). A range of lexical items
provides children with the ability to build a text and provide the basic
infrastructure of text meaning (see Berninger et al., 1997).
A recent comparative study of adolescents with dyslexia, those with
language impairment, and typically developing matched adolescents
demonstrated the ways in which different profiles of language skills can
impact writing performance (Puranik, Lombardino, &Altman, 2007).
Participants with SLI (but not dyslexia) produced fewer words and
numbers of ideas than typically developing peers. In contrast, both
students with dyslexia and students with language impairment produced
more spelling and grammatical errors than their matched peers. Puranik
and colleagues argued that the difference between the performance of
these two groups was due to the difficulties experienced by the students
with language impairment in the nonphonological dimensions of text
production.
Difficulties with literacy compromise the developmental
trajectories of children with SLI. The combined effect of language and
literacy difficulties typically results in reduced educational
attainments (Dockrell, Lindsay, Palikara, & Cullen, 2007). However,
the ways in which language and literacy interact to support writing
require further clarification if theoretical models are to address the
nature and extent of the children's difficulties and appropriately
targeted interventions are to be developed.
Compared to studies examining the reading profiles of children with
SLI (Kelso, Fletcher, Lee, & Kelso, 2007; McArthur, Hogben, Edwards,
Heath, & Mengler, 2000), investigations into their difficulties with
writing are relatively recent. The few published studies that have
examined the written texts of children with SLI provide a mixed picture
of the factors that limit the production of written text. Between the
ages of 7 and 11, children with SLI produce a high number of spelling
errors (Bishop & Clarkson, 2003)--particularly phonological errors
(Mackie & Dockrell, 2004)--and error patterns deviate from those of
chronological age but not language-age-matched peers (Mackie &
Dockrell). Children with SLI also show an increased level of grammatical
errors in the written form (Gillam & Johnston, 1992; Scott &
Windsor, 2000; Windsor, Scott, & Street, 2000). However, the most
common associated problems are not grammatical difficulties but problems
with spelling and punctuation, as well as poorer semantic content
(Bishop & Clarkson).
To date, studies of individuals with language impairment point to a
delay in patterns of writing development, where the factors that
constrain text production are similar to those experienced by younger
typically developing children. Over time, for typically developing
children, idea generation and the translation of those ideas into
written text production become more automatic, allowing time for the
cognitively demanding processes of planning and revision. In addition,
the relationships between reading and writing change. Studies of the
writing skills of students with SLI have failed to examine developmental
changes. Important gaps remain in our understanding of the writing
profiles of children with SLI and the factors that underpin difficulties
in text production. Specifically, evidence examining the writing
performance of adolescents with a history of SLI is missing and the ways
in which earlier language and literacy skills contribute to the
development of text production over time is unexplored. A further major
omission, given the motor incoordination difficulties experienced by
many children with SLI (Hill, 2004), is the lack of measures of
handwriting fluency. Transcription skills uniquely predict compositional
fluency throughout the elementary grades (Graham, Berninger, Abbott,
Abbott, & Whitaker, 1997) and motor incoordination can impact
handwriting fluency (Graham, Struck, Richardson, & Berninger, 2006);
students with a history of SLI may be disadvantaged in written text
production by transcription skills, their semantic competence, and their
literacy levels.
PURPOSE
The current study aimed to address the ways in which measures of
language, literacy, and processing limitations are related to writing,
by studying a sample of adolescents with a history of SLI. No
longitudinal data about the writing skills of students with SLI at this
phase of education have previously been published. We predicted that,
similar to other groups of children with learning disabilities, students
with a history of SLI would continue to exhibit difficulties in
producing written text in late adolescence. Given the processing demands
of producing written text, performance would be differentially impaired
in relation to oral language and reading. We expected their texts to be
short and marred by both spelling and grammatical errors. Some relative
growth in writing skills might be possible, given that previous studies
have found a relative improvement in the production of written story
composition towards the end of elementary school (Fey et al., 2004).
This slow growth may continue into the secondary school years. However,
we predicted that performance would be influenced both by previous
levels of written language and by concurrent language abilities, as well
as limitations in transcription skills. In addition, the relationships
between oral language and reading (Wise et al., 2007) led us to predict
that over time students' writing performance would be mediated by
their levels of reading.
To test these predictions, a cohort of adolescents that had been
identified with SLI at 8 years 3 months (and followed for the subsequent
8 years) completed a battery of language and literacy tests, cognitive
measures, and a handwriting fluency measure at age 16. We assessed
writing skill through the analytic scoring scale for the writing measure
of the Wechsler Objective Language Dimensions (WOLD; Wechsler, 1996;
Rust, 1996) and computed measures of text length given the relationships
between text length and quality for elementary school students (Gansle,
Noell, VanDerHeyden, Naquin, & Slider, 2002; Graham et al., 1997).
We predicted that limited expressive language would reduce text length
and thereby reduce the performance of older students with a history of
SLI. We used hierarchical regression and path analysis to examine the
pattern of relationships among language, literacy, and writing measures
both concurrently and over time to produce a model of the factors
supporting text production.
METHOD
PARTICIPANTS
Following a survey of educational provision in two local education
authorities (LEAs) in the United Kingdom, our research team asked
professionals (speech and language therapists, educational
psychologists, and special educational needs coordinators) to identify
children at age 8 who had a discrepancy between their level of
functioning in the area of speech and language and that which would be
expected given the child's functioning in other areas, and who were
also experiencing significant language-based learning needs. This
process identified a total of 133 children (Dockrell & Lindsay,
2000), from which we derived a subsample from each LEA (N = 59). We
excluded children with any additional complicating factors that might
preclude the diagnosis of SLI, and included children in two regional
special schools for children with SLI in the study (N = 10).
The resulting participants (N = 69, 17 girls and 52 boys) had been
identified as having SLI at a mean age of 8 years 3 months (SD = 4
months). All participants had English as their only language and were of
white English background. Eleven percent of the total sample was
eligible for free school meals, a measure of disadvantage in England
(Strand & Lindsay, in press), comparable to the national school
average of 14.3%. All participants required special education support to
access the curriculum, and 54% had a statement of special educational
needs (SEN) under the Education Act for England 1996. The SEN, similar
to an individualized education program in the United States, specifies
the provision that must by law be made to meet the child's unique
educational needs. This status is applied to about 3% of students in the
United Kingdom, over half of whom attend mainstream schools.
Participants were assessed an additional four times as part of a
wider longitudinal government-funded study charting the educational and
social needs of children with SLI (Dockrell, Lindsay, Palikara, et al.,
2007; see Table 1 for mean age at assessment and skills assessed). The
longitudinal study also examined the students' production of
written text at age 11 (Dockrell, Lindsay, Connelly, et al., 2007), 14,
and 16--data reported here.
As Table 2 shows, at the end of formal education the students
continued to experience difficulties with oral language and literacy.
The continued specificity of their difficulty is evident from the
statistically significant differences with nonverbal ability.
We attempted to contact all participants in their final year of
compulsory education (age 16). Sixty-two students out of the original 69
agreed to complete formal assessments; 58 agreed to complete the writing
task (15 girls and 43 boys). Of the students who refused to write, 3
completed reading and language measures. Refusers typically achieved
lower scores on language and literacy measures, but there were no
statistically significant differences between the two groups.
The children who completed writing assessments were being educated
in a variety of ways: 35 in mainstream classes, 8 in special units
within mainstream schools, and 15 in special schools including
residential schools for children with SLI. Over the previous 8 years, a
significant proportion of the participants had moved between different
types of provision. As was the case at previous points in the study
(Dockrell & Lindsay, 2008) there were few differences between
participants in different settings on the psychometric measures.
Students in specialist settings scored significantly lower on measures
of reading comprehension, F(1, 57) = 6.112, p = .02, [eta][p.sup.2] =
.10, formulated sentences, F(1, 57) = 4.498, p = .04, [eta][p.sup.2] =
.08, and nonverbal ability, F(1, 57) = 4.995, p = .03, [eta][p.sup.2] =
.08, but not on any other language (vocabulary, receptive grammar,
listening to paragraphs) or literacy (single word reading, fluency or
spelling) measures.
MATERIALS
We identified measures to tap oral language skills, literacy,
nonverbal ability, and written language, and selected tests that were
age and culturally appropriate and standardized with measures of
reliability and validity. All measures are commonly used for the
identification and assessment of children with SLI in the United
Kingdom. Measures of reliability and validity are reported for each
scale on first mention, and unless otherwise stated information was
gained from technical manuals and refers to the overall reliability and
validity.
Nonverbal Ability. The British Ability Scales II (BAS II) Matrices
subtest (Elliott, Murray, & Pearson, 1997), presents children with a
set of patterns where one pattern is incomplete. There is a choice of
six responses and children are required to point to the missing piece:
reliability, .85; validity with the Wechsler Intelligence Scale for
Children (WISC-III; Wechsler, 1991) performance scale, .47.
Receptive Vocabulary. In the British Picture Vocabulary Scale
(BPVS; Dunn, Dunn, Whetton, & Burley, 1997), children are shown four
line drawings and asked to point to the one that best illustrates a word
spoken by the investigator: reliability, .89; validity with the
Expressive One-word Vocabulary test (Gardner, 1990), .72.
Grammar. In the Test of Reception of Grammar (TROG; Bishop, 1983),
children are shown four pictures and the investigator reads a sentence.
The child selects a picture that matches the sentence structure:
reliability, .88; validity with the Clinical Evaluation of Language
Fundamentals: Revised UK Edition (CELF-[R.sup.UK]; Peers, Lloyd, &
Foster, 1999), .53.
The CELF-[R.sup.UK] (Peers et al., 1999) Formulated Sentences
subtest requires a child to produce a sentence in response to an orally
presented single word or two-word combination: reliability, .82;
validity with other CELF-[R.sup.UK] expressive subscales, .43-.49. The
Listening to Paragraphs subtest requires the child to attend to a short
paragraph and answer specific questions related to the content:
reliability, .74; validity with other receptive scales, .30-.43
Reading Decoding. The BAS II Word Reading scale (Elliott et al.,
1997) assesses recognition and oral reading of single words:
reliability, .93; validity with Wechsler Objective Reading Dimensions
reading scale, .71 (WORD; Wechsler, 1993). The Test of Word Reading
Efficiency (TOWRE; Torgesen, Wagner, & Rashotte, 1999) contains two
subtests. The Sight Word Efficiency (SWE) subtest assesses the number of
real printed words that can be accurately read within 45 sec, and the
Phonetic Decoding Efficiency (PDE) subtest measures the number of
pronounceable printed nonwords that can be accurately decoded within 45
sec: interscorer reliability, .99; test-retest reliability, .90 and
above; validity, .92-.94 SWE and .89-.91 PWE (Woodcock Reading Mastery
Scales-Revised, Woodcock, 1987).
Reading Comprehension. The WORD Reading Comprehension scale
(Wechsler, 1993) measures the student's understanding of short
written passages of text. With this test, the child reads a passage out
loud or silently and then answers comprehension questions posed orally
by the examiner. The measure has a split-half reliability for children
age 15 to 16 of .82
Spelling. The BAS II Spelling scale (Elliott et al., 1997) provides
a number of phonetically regular and irregular words to assess the
child's ability to produce correct spellings. Each item is first
presented in isolation, then within the context of a sentence, and then
again in isolation. The child has to respond by writing the word:
reliability, .91; validity with WORD Spelling (Wechsler, 1993), .63.
Written Language. The WOLD Writing Expression test (Wechsler, 1996;
Rust, 1996) requires children to write a letter describing their ideal
house. Children are allowed 15 min to complete the task. The written
output can be scored either holistically or analytically: reliability,
.89, correlation with Woodcock-Johnson Psycho-Educational
Battery-Revised (Mather & Jaffe, 1996) Dictation = 0.72. The
analytic scale comprises six dimensions, each rated on a 4-point scale,
which are scored independently of each other: ideas and development;
organization, unity and coherence; vocabulary; sentence structure and
variety; grammar and usage; and capitalization and punctuation.
Writing Fluency. Our handwriting fluency task (based on Berninger,
Mizokawa, & Bragg, 1991) requires students to write out the letters
of the alphabet, in lower case, in order; as quickly as possible in 1
min. Letters are only counted towards a total number of letters per
minute if the letters are in the correct order and legible. The task has
an interrater reliability of r = 0.97 (Berninger et al., 1997). It has
been incorporated into the Process Assessment of the Learner[TM]
(PAL[TM]) Test Battery (Berninger, 2001), where it has been shown to
conform fully with psychometric standards of reliability and validity.
PROCEDURE
Schools, parents, and participants provided informed consent prior
to any testing. A qualified educational psychologist assessed each
student individually in a quiet room at school over 3 days. The first
session involved a familiarization with the assessor and a discussion
about the longitudinal study. Participants were allowed to terminate the
session or opt out of a test if they wished. All tests were administered
using the standard procedures in the manuals. Participants received a
certificate of merit for participation in the study.
For the writing measure (WOLD; Wechsler, 1996), assessors noted the
time taken to produce the written text in seconds and participants were
asked to read back their written texts to prevent penalizing children
who were poor spellers; Unclear words were noted on a separate sheet.
Two research assistants performed reliability checks for the six
dimensions of the analytical scoring of the WOLD. In the case of an
interrater disagreement, the scores were further discussed with the
research team and informed the final scoring of the texts. Mean
interrater reliability for a randomly selected 36 ratings was 80% with a
Kappa score of .66. The research assistants counted spelling errors and
the total number of words produced, excluding numerals. There was 100%
agreement between raters for these measures.
RESULTS
We report data only for children completing the writing measure at
age 16 (N = 58). To normalize performance on the test we transformed
each standard score, the centile or T score, to a z score to provide a
common metric for analysis. In this section, we first examine student
performance in written text production, both on the total analytic score
of the WOLD (Wechsler, 1996) and in terms of words written and errors
produced. We then describe the relationships between language and
literacy and the total analytic score on the WOLD. To consider further
the different relationships between the variables, we present two path
analysis models to examine the magnitude and significance of the
relationships between literacy, language, and written text production
concurrently and over time.
STUDENT PERFORMANCE IN WRITTEN LANGUAGE AT 16
As a group, the participants performed poorly on the total analytic
scale of the WOLD (Wechsler, 1996) with a mean z score of -2.20 (SD =
1.14); this pattern of performance did not vary by gender (girls M =
-2.34, SD = .89; boys M = -2.15, SD = 1.21; t = 0.58, df = 56, ns) or
special and mainstream settings (mainstream M = -2.00, SD = 1.21;
special M = -2.50, SD = .98; t = 1.6 df = 56, ns). As such, all further
analyses treat the participants as one group.
Performance on the written language measure was significantly
poorer than the students' nonverbal ability scores (t = 9.12, df =
56, p < .0005, Cohen's d = 1.31). We examined the extent to
which performance in writing was commensurate with language and literacy
assessments through a series of repeated measures ANOVAs. Performance on
the written language measure was poorer than performance on the oral
language measures, F(3, 168) = 51.89,p < .0005, [eta][p.sup.2] = .48.
Post hoc comparisons, adjusting for multiple comparisons, indicated that
performance on the written language measure was significantly poorer
than both vocabulary and listening to paragraphs (p < .0005), but did
not differ significantly from the expressive language measure, recalling
sentences. We also considered the literacy measures of spelling, reading
decoding, and reading comprehension in relation to writing. There was a
significant effect of literacy measure, F(3, 159) = 8.336, p < .0005,
[eta][p.sup.2] = .14. Post hoc comparisons adjusting for multiple
comparisons indicated that performance on the written language measure
was significantly poorer than spelling (p = .001), reading decoding (p =
.005), and reading comprehension (p < .0005). Participants thus
experienced significant difficulties in the production of written text;
the degree of impairment for writing, as measured by norm-referenced
tests, was significantly greater than their difficulties with receptive
oral language and other aspects of literacy.
We examined written texts in terms of text length, writing time,
and spelling errors. Participants produced short texts; the mean length
of texts produced was 86 words (range 12-182). Of the 15 min allocated
for the task, participants wrote for an average of 10 min (range 2-15).
There were high and statistically significant relationships between text
length and writing time (r = .55, p < .0005) and between text length
and the WOLD (Wechsler, 1996) z score (r = .66, p < .0005). On
average, participants produced 9 words per minute (SD = 4.5). Spelling
errors in the text were frequent (M = 5.5, 3D) = 4.2; range 0-17) but
there were no significant correlations between the numbers of spelling
errors and the numbers of words written (r = -.10, ns) or WOLD total
score (r = .04, ns).
Participants produced a mean rate of 53.75 (SD = 27.61) letters per
minute for the handwriting fluency measure. The mean number of letters
per minute produced was equivalent to that of children between 8 and 9
years old (Grade 3 M = 47.3; Grade 4 M = 63.26; Graham, Berninger,
Weintraub, & Schafer, 1998). Handwriting fluency at 16 years was
significantly and positively correlated (r = .54, p = .002) concurrently
with the WOLD reading and spelling z scores, and at 14 with the reading,
spelling, and nonverbal ability z scores. Writing fluency was
significantly correlated with both the numbers of words written (r =
.54, p < .0005) and WOLD z score (r = .42, p < .0005), but there
was no relationship with the numbers of spelling errors produced (r = .
18, ns).
Analytic Scores. To identify specific patterns of difficulties, we
examined the analytic scores of WOLD (Wechsler, 1996) subtests. The best
performances were on measures of grammar (M = 1.71, SD = .88) and
capitalization (M = 1.67, SD = .85), "although both means were
still at the lower end of the scale. The poorest performance was on the
measure of sentence structure (m = 1.45, SD = .73), a score indicative
of poor sentence structure containing many errors that inhibit clarity
or fluency (Rust, 1996). Measures of ideas and development (M = 1.5, SD
= .73), vocabulary (M = 1.47, SD = .73), and organization and coherence
(M = 1.57, SD = .79) were also in the low range. A Freidman's
Analysis indicated that the scores differed statistically significantly
across the subtests ([chi square] = 25.86, df = 5, p < .0005).
Measures of grammar and capitalization did not differ from each other (z
= .564, ns). There were significant differences between grammar compared
with organization and coherence (z = -2.138, p = .03), ideas and
development (z = -2.558, p = .01), vocabulary (z = -3.500, p <
.0005), and sentence structure (z = -3.638, p < .0005). Scores for
capitalization were significantly better than vocabulary (z = -2.683, p
= .007) and sentence structure (z = -3.153, p = .002), but did not
differ statistically from the measures of ideas and development (z =
-1.908, ns) or organization and coherence (z = -1.414, ns). The measure
of organization and coherence was significantly better than vocabulary
(z = -2.121, p = .03) but did not differ from ideas and development (z =
-1.00, ns) or sentence structure (z = -1.748, ns). Ideas and
development, vocabulary, and sentence structure did not differ
significantly from each other (z = -.577, ns; z = -.832, ns; z = -.302
ns).
We computed a factor analysis to investigate further the pattern of
subtest relationships. The factor analysis met all the necessary
statistical assumptions; we considered only those factors with
eigenvalues greater than 1.0. The analysis generated a single factor
solution accounting for 83% of the variance. There were large and
significant loadings (.87) for all of the WOLD (Wechsler, 1996)
subtests.
Writing Trajectories Over Time. Data for the total analytic score
of the WOLD (Wechsler, 1996) were available for 51 participants at four
time points (ages 11, 12, 14, and 16). Four participants had refused to
write at 11, and data were missing for 1 student at age 12 and 2
participants at age 14. There was no significant difference between
writing scores at age 16 for participants with missing data (M = -2.66)
and those with data for all four time points (M = -2.14, t = 1.159, df =
56, ns). As Figure 1 shows, there was a significant decrease in relative
performance as measured by z scores, F(3, 150) = 23.888, p < .0005,
[eta][p.sup.2] = .32. Post hoc comparisons of z scores adjusting for
multiple comparisons indicated that the participants' writing
performance at age 11 was significantly better than their performance at
age 12 (p = .002), 14 (p = .002), and 16 (p < .0005). Performance at
age 12 and age 14 did not differ whereas there was a significant decline
in performance again at age 16 (p < .0005 for both ages 12 and 14).
[FIGURE 1 OMITTED]
Although the mean drop between ages 11 and 16 was one SD (M = 1.0),
patterns of change varied across participants. A change score was
computed where the z score at age 11 was subtracted from the z score at
age 16, thereby providing a pattern of change across 5 years, where
positive scores would indicate a relative increase in writing
performance. Table 3 presents the relationships between literacy,
language, and nonverbal abilities and change scores. Using a Bonferroni
correction of .004 for multiple correlations there were significant
relationships between WOLD change score handwriting fluency (r = .54, p
< .0005; Wechsler, 1996) and spelling (r = .38, p = .006). There were
no significant relationships with nonverbal ability, vocabulary, reading
decoding, and reading comprehension. We examined this pattern of
relationships using multiple regression. In all cases residuals were
normally distributed. The extent of the relationship between gain score
and handwriting fluency was confirmed with a multiple regression
controlling for nonverbal ability which revealed a significant model,
F(2, 49) = 9.689, p < .0005) accounting for 29% of the variance.
Fluency was the only significant predictor in the model ([beta] = .479);
the less fluent students were in producing the alphabet the more likely
were their writing scores to decrease (in relation to their peers) over
time.
RELATIONSHIPS BETWEEN LANGUAGE, LITERACY, AND THE WOLD
There were statistically significant correlations for the WOLD z
score (Wechsler, 1996) at age 16 and all the predictor variables apart
from the TROG (Bishop, 1983). As expected, the literacy measures of
spelling, reading decoding, and reading comprehension were significantly
related to writing. In addition, the language measures of vocabulary
(BPVS; Dunn et al. 1997) and formulated sentences were statistically
significantly related and each correlated with reading decoding and
comprehension.
We predicted that the most significant influence on students'
writing would be previous levels of writing, but that vocabulary and
reading levels would account for additional variance (Dockrell, Lindsay,
Connelly, et al., 2007). Three sequential multiple regression analyses
examined prediction of WOLD writing (Wechsler, 1996) at age 16. In the
first analysis, we entered writing at age 14 into the model as the first
step to control for previous written language performance. On the second
step, we entered vocabulary, resulting in a significant increase in
[R.sup.2] (significant F Change, p = .001); on the third step, single
word reading again resulted in a significant increase in [R.sup.2]
(significant F Change, p = .005). The full model [R.sup.2] is shown in
Table 4 and was significant, F(3, 57) = 20.624, p < .0005, adj
[R.sup.2] = .53.
The second sequential multiple regression used word reading
efficiency (TOWRE; Torgesen et al., 1999) as the predicting literacy
variable. We reasoned that for later literacy, fluency in word reading
and phonological decoding were likely to have greater impacts on the
production of written text than untimed measures of single word reading.
There was no statistically significant difference between the
participants' performance on single word reading efficiency and
phonemic decoding efficiency (reading efficiency M = 69, SD = 27;
phonemic decoding efficiency M = 71, SD = 30, t = -1.871, df = 58, ns).
As in the previous analysis, writing at age 14 was entered into the
model to control for previous written language performance, followed by
vocabulary. In this case, entering the TOWRE as the third step resulted
in a significant increase in [R.sup.2] (significant F Change, p = .003).
The full model [R.sup.2] is shown in Table 5 and was significant, F(3,
57) = 21.624, p < .0005, adj [R.sup.2] = .52, with all variables
having significant effects. Thus, the impact on writing of both reading
fluency and single word decoding reading measures was similar.
Both the differential correlations between spelling and the other
variables and analyses highlighting the importance of writing fluency
indicated that their relative roles in writing performance should be
considered. Thus, we employed a third sequential multiple regression
analysis to examine the impact of these variables. As in the previous
models, WOLD writing (Wechsler, 1996) at age 14 was entered into the
model followed by vocabulary and reading. On the fourth step, we added
writing fluency but this did not significantly change the model
[R.sup.2] (F Change, p = .24). On the fifth and final step, we entered
spelling, which resulted in significant increase in [R.sup.2]
(significant F Change, p = .001). The full model [R.sup.2] was
significant, F(5, 58) = 18.891, p < .0005, adj [R.sup.2] = .61. As
Table 6 shows, reading efficiency and writing fluency did not have a
significant partial effect in the full model, but previous WOLD score,
vocabulary, and spelling did have significant partial effects.
PATH ANALYSES
The regression analyses clarified the relationships between
language, literacy, and writing. We tested two path analysis models in
order to examine the relative importance of oral language and literacy
on the participants' writing scores. The regression analyses had
indicated that large effect sizes were to be predicted and that, with
appropriate parameter estimates and tests of alternative models, the
small sample could be used to build an exploratory path model using
maximum likelihood estimation (Ullman, 1996). The stronger the
correlations, the more power there is to detect an incorrect model, and
this would reduce Type 1 errors in the models.
[FIGURE 2 OMITTED]
We used Amos 7.0 to test the models. Model 1 examined concurrently
the relative contribution of language, literacy, and writing speed at
age 16. Model 2 examined the longitudinal effects of language and
literacy from age 8 to age 16. A variety of fit indices are available
with Amos. The overall fit of the final model was assessed by [chi
square] and by root mean square error of approximation (RMSEA).
Following Hu and Bentler (1999), who recommend joint criteria to retain
a model, we only considered models a good fit if the [chi square] was
not significant, RMSEA < .06 and CFI > .96 (RMSEA and CFI being a
more sensitive fit index with small sample sizes; Fan, Thompson, &
Wang, 1999).
For the concurrent model we predicted that spelling, vocabulary,
and speed of writing would have direct effects on writing at age 16,
with reading revealing an indirect effect at this point through
spelling. We also predicted that both vocabulary and reading would be
associated. As predicted, the path analysis in Figure 2 indicates a
direct relationship between vocabulary and writing ([beta] = .32), speed
of writing ([beta] = .21) and spelling ([beta] = .47). Reading fluency
revealed an indirect effect on writing through both spelling ([beta] =
.58) and speed of writing ([beta] = .57). The goodness of fit measures
indicated a good fit: [chi square] (4) = 3.602, p = .46, RMSEA = .00,
CF1 = 1.000. We also tested models, including nonverbal ability and
reading comprehension, to eliminate potentially relevant factors. These
models failed to provide a fit with the data.
[FIGURE 3 OMITTED]
For the exploratory predictive path analysis, we considered
measures assessed at ages 8, 11, and 14 and writing at age 16. We
predicted that vocabulary and reading at age 8 would be significant
factors in supporting writing at age 11 and that from age 11 writing,
itself, would show the strongest relationships with subsequent writing
performance. No model including reading at age 8 or reading at age 11
fit the data; however, a longitudinal model including vocabulary at age
8 having an indirect effect on writing provided a good fit. The path
analysis in Figure 3 indicates direct effects of reading ([beta] = .27),
spelling ([beta] = .34), and writing ([beta] = .32) at age 14 with
writing at age 16. Oral language skills had an indirect effect through
reading at age 14 ([beta] = .34) and writing at age 14 ([beta] = .25).
Vocabulary at age 8 revealed indirect effects on writing through
vocabulary at age 11 ([beta] = .75). Moreover, vocabulary at age 11
revealed indirect effects on writing at age 16 through oral language at
age 14 ([beta] = .51). More important, the indirect effect of writing at
age 11 was evident through spelling at age 14 ([beta] = .55) but not, as
predicted, writing at age 14 ([beta] = .16). The goodness of fit
measures indicated a good fit: [chi square] (16) = 11.350, p = .79,
RMSEA = .00, CF1 = 1.000. We also tested models examining alternative
directions of effect and models including nonverbal ability and reading
comprehension to explore a better fit. These alternative models did not
provide a fit with the data.
DISCUSSION
We examined longitudinally the writing skills of a cohort of
students with a history of SLI to age 16. We examined measures of
language and literacy assessed both longitudinally and concurrently to
establish their relative contribution to written text production. The
students in this study continued to experience specific difficulties
with language and literacy. Production of written text continued to be
an area of marked vulnerability, with writing scores being the lowest
standardized score of the receptive language and literacy measures.
Moreover, during their teenage years the students' writing skills
decreased relative to standardized norms. Thus, the current data
contrast with data in the elementary years for children with SLI where a
relative improvement in the production of written story composition has
been noted (Fey et al., 2004). These differences are important to
address. The decreases in student performance on written measures may
reflect specific language difficulties. For typically developing
children, increasing language and literacy skills support later
development of writing; for those with continued difficulties these
resources are not available. In conjunction it is important to consider
the specific support provided to children when developing their written
language skills. This decrease in writing skills occurred at the time
(age 11) when, in the United Kingdom, it is expected that students have
mastered the basic skills in reading and writing, have moved towards the
analysis of genres, are writing with technical accuracy, and able to
organize text into planned and coherent sequences (Department for
Children, Schools and Families, n.d.)--a major challenge for the
students in this study.
WOLD (Wechsler, 1996) provided the tool for comparing performance
on writing dimensions over time. Results on the WOLD subscales at age 16
were consistent with assessments at previous points in development
(Dockrell, Lindsay, Connelly, et al., 2007; Mackie, 2007): Performance
was reduced across all subscales, but the poorest performance was
evident in measures of sentence structure, ideas and development, and
vocabulary. The factor analysis of the WOLD subscales provided evidence
that at this point in development, the students' written work could
be captured by a single dimension. This differs from the patterns at age
11 (Dockrell, Lindsay, Connelly, et al., 2007) and age 14 (Dockrell
& Connelly, 2007), where two different dimensions underpinned
performance on the WOLD: semantics and rules. This single factor for the
WOLD is, however, consistent with data for younger (age 11) typically
developing children (Connelly & Dockrell, 2008) and suggests that
for students with a history of SLI the coordination of idea generation
and sentence production and grammar is an extended developmental
process.
Despite the apparent coordination of the two dimensions,
difficulties in relation to form (spelling and handwriting), and content
generation still posed major difficulties for the students in our study.
Texts produced were short with frequent spelling errors. Previous
research has failed to consider writing fluency for students with SLI,
and current data indicate that shorter texts are associated with reduced
levels of handwriting fluency. Indeed, the cohort's handwriting
fluency was equivalent to the average obtained for students some 7 years
younger (Graham et al., 1998). This is consistent with slow production
of text, as evidenced by words produced per minute. The less fluent
students were also more likely to show decreases in their writing
standard scores over time.
Regression analyses revealed that at age 16 the significant
concurrent predictors of text production were spelling and vocabulary.
The importance of vocabulary as a key predictor of text production at
this age extends work with younger students which has identified
limitations in text generation and reduced levels of word use and
lexical diversity (Fey et al., 2004; Scott & Windsor, 2000) and
semantic content (Bishop & Clarkson, 2003) as critical limiting
factors for children with SLI. The continuity of the importance of
vocabulary as a determinant of text quality for this cohort of children
(Dockrell, Lindsay, Palikara, et al., 2007) adds further weight to the
view that vocabulary provides a building block for written language.
The poor spelling skills of the participants were evident both in
their written text productions and when assessing their single word
spellings. At age 11, the participants' writing levels were
mediated by their reading levels. The point of fracture has moved, and
on the surface appears similar to difficulties exhibited by young adults
with dyslexia (Connelly et al., 2006), where writing was constrained by
transcription skills (in the form of poor spelling and slow
handwriting). However, the Connelly et al. population was different from
the current cohort in that they could produce compositions that were age
appropriate in terms of ideas and development, sentence structure and
organization, unity, and coherence scales of the WOLD (Wechsler,
1996)--all areas of weakness for the students described here. As shown
by Puranik et al. (2007, with a younger cohort), problems with spelling
and transcription combined with wider problems with language led to very
poor performance in writing.
Given the relationships between the different variables and the
predictions derived from previous studies, we used path analysis to
provide estimates of the magnitude and significance of hypothesized
causal connections between sets of variables. Our first model explored
the potential interactions between concurrent measures. The best-fit
model included direct effects of vocabulary, spelling, and writing
fluency, with reading fluency (a timed measure of reading decoding)
having an indirect effect through spelling and writing fluency. The
concurrent model confirms both the effects of semantic factors (as
measured by vocabulary) and phonological factors (as measured by
spelling), and suggests an independent contribution of writing fluency.
There has been a longstanding concern about the information
processing constraints experienced by children with SLI (Ellis Weismer
& Hesketh, 1996; Montgomery, 2000), and their reduced performance on
tasks requiring quick and accurate performance (Leonard et al., 2007).
Measures of speed of writing and reading fluency are both significantly
related--either directly or indirectly--to text production. These
deficits may reflect reduced performance in both verbal working memory
(reading fluency) and processing speed (speed of writing; see Leonard et
al.). Yet the highly significant relationship in the current study
between the two (.57) suggests that the underlying factor may be the
ability to coordinate and efficiently manage different information, and
this limits children's text production. This interpretation would
also be consistent with the difficulties experienced by children with
language impairment in monitoring and editing their written productions
(Scott, !999). As long as translating continues to place heavy cognitive
demands on writing, management of planning will be impaired.
In our second model we explored the longitudinal predictors for the
participants' writing performance at age 16. This model identified
direct effects of reading, spelling, and writing at age 14 on writing at
age 16. These data demonstrate the ways in which both phonological and
morphological literacy measures come to the fore in the writing
performance for these students. As in the regression models,
nonphonological factors were also evident and, unlike the literacy
measures, their impact was traced back to age 8. Vocabulary appears to
provide an indication of the semantic knowledge which supports both
writing at age 11 and sentence formulation at age 14. Over time, both
reading and writing skills mediate the impact of oral language.
The concurrent and the longitudinal models both provide evidence to
support specific student-based factors that impinge on the production of
written text, and offer scope for targeted and strategic interventions
(Troia, 2006) and interventions which could compensate for text
production difficulties (MacArthur, in press). It is unlikely that these
factors alone explain the relative decline in writing performance. As
the change scores demonstrate, only writing fluency predicted
change--and this factor accounted for 29% of the variance. An important
question remains about the support in writing that is provided once
students enter secondary school, both to maintain current levels of text
production and to enhance their capacity to produce texts closer to
expected targets. Support for those who struggle at this phase of
education in England is "uneven" (Office for Standards in
Education, Ofsted, 2007, [paragraph] 75, page 31), and differentiation
of the curriculum often involves simplifying activities (Dockrell &
Lindsay, 2007). Government initiatives to improve skills at this stage
have not been successful, with less able children being left behind and
catch-up classes for those who struggled in primary school failing to
bring students up to the expected standard (Ofsted). Typically these
interventions focus on word reading and are provided for most students
aged 12 to 14. Thus, given evidence from both the school reports for
these students (Dockrell, Lindsay, Palikara, et al., 2007) and the
current educational context, it is unlikely that students with SLI are
receiving the support they require to develop their writing skills. A
lack of appropriate interventions and support resources further
disadvantages these struggling writers. This lack of support has been
highlighted in other educational systems (see Moni et al., 2007; Troia
& Maddox, 2004).
STUDY LIMITATIONS
Investigations of written language are complex and subject to a
number of limitations. The current study is limited by the small sample,
the use of a single writing measure, and the lack of information on the
children's wider information processing skills. Given the purported
importance of vocabulary a more detailed examination of the
students' competence in this area is needed. It is not clear the
extent to which the vocabulary measure is tapping the breadth of the
children's knowledge, the depth of their semantic representations,
or the efficiency of lexical retrieval. There is increasing evidence
that measures of depth and breadth of vocabulary may have differential
effects on reading, and we expect similar patterns to be evident in
writing (see, e.g., Ouellette, 2006; Tannenbaum et al., 2006). Future
work should pay specific attention to the nature of the evidence for
interventions provided to support writing, including the skills that
underpin performance in writing and the strategies provided for
coordination of these skills.
Care also needs to be taken in generalizing performance on our
writing task. The decline in writing scores could be explained by a lack
of emphasis on this kind of writing in secondary school. Studies of more
complex writing tasks demanded by the secondary school system might lead
to fewer problems. However, the very poor level of the
participants' performance on English exams suggests that this is
unlikely to be the case (Dockrell, Lindsay, Palikara, et al., 2007).
Although the data suggest widespread failure with writing tasks in
relation to peers, the importance of examining writing profiles and
predictors of writing performance across genres remains an important
avenue of further research.
EDUCATIONAL IMPLICATIONS
The current study highlights the importance of phonological and
nonphonological dimensions of oral language as important factors in
supporting (or limiting) the production of written text. In addition, we
identified writing fluency as a particular problem for these students.
Further automating the processes involved in transcription is an
important consideration; a recent UK-based intervention to improve the
spelling of subject-specific words by students with dyslexia (Sterling,
Ertubey, Brownfield, O'Reilly, & Noyce, 2004) seems a step in
the right direction. Other schemes that have been used successfully with
other children-those that do not advocate lower-level writing
instruction at the expense of higher-level writing skills--could also be
potentially adapted for use with students with SLI (see Berninger et
al., 1997). We have shown that the writing produced by these students is
directly related to literacy level; schemes to improve literacy levels,
particularly spelling, should also have a long-term benefit provided
they are embedded within interventions that support the coordination of
text production and meaning generation.
In addition, there is a need to consider the vocabulary that these
students possess to support idea generation. Previously we have argued
that the development of semantic skills may be seen as a compensatory
mechanism to support the writing instruction for students with SLI
(Dockrell, Lindsay, Connelly, et al., 2007). The data presented here
confirm that this is a continuing issue as children become older.
Students with poor vocabulary skills will need explicit support with
vocabulary to generate ideas; this dimension is particularly important
because we identified no changes in the participants' relative
vocabulary across their education (Dockrell, Lindsay, Connelly, et al.,
2007).
Finally, an important consideration for students who have
experienced such a history of failure to write will be motivation.
Interventions will need to be developed which both address the major
limitations with basic skills and motivate the young people within an
empowering educational environment. This remains a major challenge.
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JULIE E. DOCKRELL
Institute of Education, University of London
GEOFF LINDSAY
University of Warwick
VINCENT CONNELLY
Oxford Brookes University
JULIE E. DOCKRELL, Professor, Institute of Education, University of
London, England. GEOFF LINDSAY, Professor and Director, Centre for
Educational Development, Appraisal and Research, University of Warwick,
Coventry, England. VINCENT CONNELLY, Senior Lecturer, Department of
Psychology, Oxford Brookes University, England.
Address correspondence to Julie E. Dockrell, Institute of
Education, University of London, 20 Bedford Way, London WC1H OAL, United
Kingdom (e-mail: j.dockrell@ioe.ac.uk).
The authors would like to thank all the students, parents,
teachers, and support staff who gave willingly of their time; the
Department for Children, Schools, and Families who funded the final
phase of the project; and all the research assistants who contributed to
different phases of the study: Becky Clark, Clare Hall, Rebecca Jeanes,
and Clare Mackie. Measures collected at age 14 for part of the sample
contributed to the doctoral dissertation completed by Clare Mackie
(2006).
Manuscript received November 2007; accepted June 2008.
TABLE 1
Assessment Points and Skills Assessed
Educational Equivalent
Mean Age Phase Phase Skills
Time (SD in months) UK U.S. Assessed
1 8 years Year 3 Elementary Language,
3 months (Key Stage 2) school literacy,
(4) nonverbal
ability
2 10 years Year 6 Elementary Language,
8 months (Key Stage 2) school literacy,
(4) Last year writing,
primary school nonverbal
ability
3 12 years Year 7 Junior Literacy,
1 month (Key Stage 3) high/middle writing
(4) Entry to school
secondary School
4 13 years Year 9 Middle Language,
11 months (Key Stage 3) school/high literacy,
(5) school writing,
nonverbal
ability
5 15 years Year 11 High school Language,
10 months (Key Stage 4) literacy,
(4) Final year writing
compulsory
education
Note. A Key Stage is one of the set stages of the national
curriculum in the United Kingdom.
TABLE 2
Mean Z Scores and Standard Deviations for Language and Literacy
Measures at Ages 14 and 16
Student
Competency Assessed Age Mean SD
Nonverbal ability (BAS z 14 -0.81 .6
score)
Receptive vocabulary (BPVS z 16 -1.23 1.12
score)
Formulated sentences (CELF z 14 -2.4 .35
score)
Listening comprehension (CELF 16 -1.14 .66
z score)
Single word reading (BAS z 16 -1.79 .99
score)
Reading comprehension (WORD z 16 -1.59 .73
score)
Spelling (BAS z score) 16 -1.69 1.07
Difference With
Competency Assessed Nonverbal Ability
Nonverbal ability (BAS z
score)
Receptive vocabulary (BPVS z F(1, 56) = 9.03, p = .004,
score) [eta][p.sup.2] = .14;
Formulated sentences (CELF z F(1, 56) = 174.48, p < .0005,
score) [eta][p.sup.2] = .76
Listening comprehension (CELF F(1, 56) = 5.90, p = .018,
z score) [eta][p.sup.2] = .10;
Single word reading (BAS z F(1, 55) = 60.49, p < .0005,
score) [eta][p.sup.2] = .53;
Reading comprehension (WORD z F(1, 56) = 60.85,p < .0005,
score) [eta][p.sup.2] = .71
Spelling (BAS z score) F(1, 53) = 43.70, p < .0001,
[eta][p.sup.2] = .45
Note. BAS = British Ability Scales II (Elliott, Murray, & Pearson,
1997). BPVS = British Picture Vocabulary Scale (Dunn, Dunn, Whetton,
& Burley, 1997). CELF = Clinical Evaluation of Language Fundamentals
(Peers, Lloyd, & Foster, 1999). WORD = Wechsler Objective Reading
Dimensions (Wechsler, 1993).
TABLE 3
Correlations Between WOLD Change Score, Language, Literacy, Cognitive
Measures, and Writing at Time 4 and Time 5
Variable 1 2 3
WOLD change score
WOLD z score (TS) .81 *
Nonverbal z score (T4) .23 .42 *
Formulated sentences z score (T4) .23 .37 * .31 *
BPVS z score (T5) .25 .55 * .52 *
Listening to paragraphs z score (TS) .36 .47 * .25
TROG z score (T5) .20 .31 .26
BAS word reading z score (T5) .34 .59 * .51 *
TOWRE--word reading efficiency z score .35 .57 * .44 *
Word comprehension z score (TS) .23 .45 * .63 *
Spelling z score (T5) .38 * .65 * .46 *
Writing fluency z score .54 * .54 * .47 *
Variable 4 5 6
WOLD change score
WOLD z score (TS)
Nonverbal z score (T4)
Formulated sentences z score (T4)
BPVS z score (T5) .54 *
Listening to paragraphs z score (TS) .40 * .47 *
TROG z score (T5) .31 .41 * .14
BAS word reading z score (T5) .38 * .51 * .19
TOWRE--word reading efficiency z score .41 * .50 * .28
Word comprehension z score (TS) .43 * .56 * .27
Spelling z score (T5) .18 .30 .08
Writing fluency z score .40 * .43 * .23
Variable 7 8 9
WOLD change score
WOLD z score (TS)
Nonverbal z score (T4)
Formulated sentences z score (T4)
BPVS z score (T5)
Listening to paragraphs z score (TS)
TROG z score (T5)
BAS word reading z score (T5) .34
TOWRE--word reading efficiency z score .29 .55 *
Word comprehension z score (TS) .29 .54 * .62 *
Spelling z score (T5) .32 .75 * .58 *
Writing fluency z score .32 .41 * .57 *
Variable 10 11
WOLD change score
WOLD z score (TS)
Nonverbal z score (T4)
Formulated sentences z score (T4)
BPVS z score (T5)
Listening to paragraphs z score (TS)
TROG z score (T5)
BAS word reading z score (T5)
TOWRE--word reading efficiency z score
Word comprehension z score (TS)
Spelling z score (T5) .41
Writing fluency z score .51 * .41
Note. WOLD = Wechsler Objective Language Dimensions (Wechsler, 1996).
BPVS = British Pictute Vocabulary Scale (Dunn, Dunn, Whetton,
& Burley, 1997). TROG = Test of Reception of Grammar (Bishop, 1983).
BAS = British Ability Scales II (Elliott, Murray, & Pearson, 1997).
TOWRE = Test of Word Reading Efficiency (Torgesen, Wagner, & Rashotte,
1999).
* p = .004 with Bonferonni correction.
TABLE 4
Predicting WOLD Writing at Age 16: The Role of Word Reading Accuracy
[R.sup.2]
Predictor Change [beta] P
WOLD z score at age 14 .326 .353 .001
Vocabulary z score at age 16 .134 .266 .018
Single word reading z score at age 16 .074 .322 .005
Note. WOLD = Wechsler Objective Language Dimensions (Wechsler, 1996).
TABLE 5
Predicting WOLD Writing at Age 16: The Role of Word Reading Efficiency
[R.sup.2]
Predictor Change [beta] P
WOLD z score at age 14 .326 .381 .001
Vocabulary z score at age 16 .134 .243 .031
Word reading efficiency z score at age 16 .081 .333 .003
Note. WOLD = Wechsler Objective Language Dimensions (Wechsler, 1996).
TABLE 6
Predicting WOLD Writing at Age 16: The Role of Reading, Writing, and
Spelling
[R.sup.2]
Predictor Change [beta] P
WOLD z score at age 14 .335 .2G4 .01
Vocabulary z score at age 16 .114 .232 .03
Word reading efficiency z score at age 16 .075 .041 .746
Writing fluency .024 .154 .167
Spelling z score at age 16 .093 .395 .001
Note. WOLD = Wechsler Objective Language Dimensions (Wechsler, 1996).